Carnegie-Rochester Conference Series on Public Policy | Macro Paper Warehouse

Discretion versus policy rules in practice

This 1993 Carnegie-Rochester Conference paper by John Taylor introduces what became known as the “Taylor rule” — a simple guideline for setting the federal funds rate, r = p + 0.5y + 0.5(p - 2) + 2, where p is inflation over the previous four quarters and y is the percent deviation of real GDP from a 2.2%-per-year trend — and argues for treating monetary policy rules as broad, “systematic and credible” approaches to policymaking rather than as mechanical algebraic formulas to be followed literally. Drawing on multicountry rational-expectations model comparisons (his own and others’), Taylor reports that interest-rate rules responding to inflation and output outperform rules targeting the money supply or a fixed exchange rate, and that a flexible exchange-rate regime dominates a fixed one on both output-stability and price-stability grounds for the G-7 countries he examined. The paper’s hypothetical policy rule, despite its deliberately round-number coefficients, is shown to track actual Federal Reserve behavior over 1987-1992 remarkably closely, with a notable exception in late 1987 when the Fed eased following the stock market crash. Taylor then works through two real episodes — the 1990 oil-price shock following Iraq’s invasion of Kuwait, and the sharp 1990 rise in long-term interest rates coinciding with German unification — to argue that departures from a rule’s literal prescription can themselves be principled and rule-consistent once policymakers correctly diagnose whether a disturbance is temporary (the oil shock, confirmed by futures prices showing only a modest expected persistent rise) or driven by real rather than inflationary forces (the German rate rise, attributable to a unification-driven investment-demand shift rather than inflation expectations).

Econometric policy evaluation: A critique

This 1976 Carnegie-Rochester Conference Series paper by Robert Lucas argues that the standard “theory of economic policy” – simulating a fixed, estimated econometric model under alternative hypothetical policies – is invalid for policy evaluation, because the model’s parameters are themselves the optimal decision rules of economic agents, and those decision rules change systematically whenever the policy regime they were estimated under changes. Lucas first documents that actual forecasting practice already departs from the textbook theory of economic policy – econometricians largely ignore pre-1947 data, frequently re-fit relationships (the wage-price sector being a running example), and revise intercepts based on recent runs of residuals – and shows that Cooley and Prescott’s “adaptive regression,” in which the parameter vector follows a random walk, matches this behavior and reconciles good short-term forecast accuracy with essentially unbounded variance for long-run policy simulations built on the same models. He then works through three canonical building blocks of large macroeconometric models – the Friedman-Muth permanent-income consumption function, a Jorgensonian tax-and-investment model in the style of Hall and Jorgenson, and an expectational Phillips curve – to show concretely that a policy change which is understood in advance by agents (e.g., an income tax surcharge announced as temporary, or an investment tax credit believed to be transitory rather than permanent) produces behavioral responses that a fixed-parameter extrapolation of the estimated relationship gets systematically wrong, sometimes by a factor of several times in the investment-credit case. The paper’s central syllogism, stated in the concluding section, is that because econometric relationships encode optimal decision rules that vary with the stochastic structure of the variables agents must forecast, “any change in policy will systematically alter the structure of econometric models,” so that comparisons of alternative policy rules using models estimated under a different, unstated policy regime are invalid regardless of how well those models fit historical data or forecast in the short run. Lucas’s proposed remedy is not to abandon policy evaluation but to model policy itself as a parameterized rule generating the forcing variables, so that the behavioral parameters become an estimable function of the policy parameters – feasible, he argues, only for policy changes that are openly discussed, understood, and expected to be enforced as stable rules, not for ad hoc or deliberately concealed interventions.

Price-Level Determinacy Without Control of a Monetary Aggregate

Woodford shows that the price level remains determinate even under two forms of radical money-supply endogeneity long thought to destroy monetary control – a central-bank interest-rate peg and unrestricted private (“free banking”) issuance of money substitutes – once one recognizes that the government’s intertemporal budget constraint, not the quantity-theoretic money-demand equation, is what pins down the price level under a “fiscal theory of the price level.” Woodford argues the quantity-theoretic tradition’s requirement that a central bank control a monetary aggregate to ensure price-level determinacy relies on an incomplete accounting of equilibrium conditions. Working in a Sidrauski-Brock representative-household monetary model, he derives, alongside the familiar money-demand (“LM”) equation, a second necessary equilibrium condition equating the real value of net government liabilities to the discounted present value of current and future primary budget surpluses, plus the interest saved on monetary liabilities. This fiscal condition lacks the homogeneity property that makes the quantity-theoretic account depend only on the ratio of money to prices, so it can determine a unique price-level path on its own whenever the fiscal regime is “non-Ricardian” – that is, whenever the government’s budget is not automatically adjusted to guarantee its own present-value balance regardless of the price path. Woodford first shows an “irrelevance proposition”: under a Ricardian-consistent fiscal rule, changes in the path of the money supply, holding the government’s fiscal position fixed, have no effect on the equilibrium price level at the date of the change, since the fiscal equation is unaffected. He then applies this reasoning to two harder cases. Under a pure interest-rate peg – the classic case Sargent-Wallace-style analyses treat as generating indeterminacy – the fiscal condition alone yields a unique positive price-level path given the paths of government purchases, tax revenue, and net liabilities. And under a “free banking” extension in which unregulated intermediaries issue interest-bearing deposits that perfectly substitute for the monetary base (subject only to an intermediation cost), the same fiscal condition continues to pin down a unique price path, so unrestricted private money creation “need pose no threat” to price-level determinacy. Woodford concludes that money-supply variations matter for the price level, under either regime, only insofar as they affect the government’s fiscal position through seignorage – not through any independent quantity-theoretic channel – so central banks need not resist interest-rate targeting or financial deregulation on determinacy grounds.

Shocks

Cochrane surveys the empirical evidence for the leading candidate shocks behind postwar U.S. business cycles – monetary policy, technology, oil prices, and credit – and concludes that none of them robustly accounts for the bulk of output fluctuations, while unforecastable movements in endogenous variables like consumption and output themselves explain a large and comparatively stable 50-70% of output variation. Working mostly through VARs, he shows for monetary shocks that estimated contributions to output variance range from as high as 82% in simple specifications down to under 10% once more “level” variables (consumption, hours), alternative orderings, and long-run restrictions are imposed, with virtually no explanatory power at horizons under a year; he argues the largest credible estimate is around 15-25% at a two-to-three-year horizon, tenuous even then. For technology shocks, Prescott’s famous calculation that 70% of output variance is technology-driven proves to be extremely sensitive to sampling error, the choice of statistic (variance decomposition versus long-horizon forecastability versus Beveridge-Nelson-detrended variance), and the production-function specification, with several re-calculations – inspired by Blanchard-Quah, Rotemberg-Woodford, and Christiano – pushing the figure down toward a small fraction of a percent; the concept of a “technology shock” is also shown, following Hansen and Prescott’s own broadening of the term, to risk becoming vacuous, standing in for essentially any distortion that lowers measured output given capital and labor. Oil-price and credit shocks receive briefer treatment and are found quantitatively too small (each explaining well under 20% of output variance in Cochrane’s VARs) despite genuine, if modest, supporting descriptive evidence. Faced with this shortfall, Cochrane examines whether unobservable “consumption” or “news” shocks – information individual agents have about their own prospects that, aggregated, forecasts future aggregate activity – can generate genuine business-cycle dynamics; he shows that a standard real-business-cycle model does not naturally produce consumption-led downturns from good news (news of future productivity growth instead triggers an immediate consumption rise and a decline in current output and labor), but that adding an explicit persistent news-shock process, or feeding VAR-based technology forecasts through the model, can reproduce the data’s characteristic transitory-output, forecastable-growth pattern. He closes by noting that if this news-shock view is correct, economists may remain permanently unable to name the true underlying causes of business cycle fluctuations.